2. I. Wildfire Risk
II. Impact Components
III. Data Sources
I. History
II. Precipitation
III. Fuel
IV. Slope
V. Wind
IV. Data Prep
V. Methodology
I. Reclassification
II. Weighted Overlay
III. Gridding
VI. Output
VII. Web Application
VIII.Future Research &
Development
Agenda
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3. • Over 32% of the U.S. population lives in the
wildland-urban interface (WUI) (U.S. Forest
Service, 2013)
• Wildfire activity for 2013 increased 50% above
average of past 4 years, doubling burn area of
2012
• Losses due to wildfire statistically result in 100%
loss to the homeowner
Wild Fire Risk
Confidential and Proprietary, Dewberry & Myriad Development, Inc.
4. • Dewberry would like to expand its business into
the home insurance sector. They have targeted a
need for higher granular quality wildfire data to
replace existing zip code levels.
• The goal: Create a 30m resolution fire model for
entirety of the U.S.
What is Wild Fire Risk?
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5. • Fire History
• Precipitation
• Fuel
• Slope
• Wind
Wildfire Impact Components
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6. • Fire History
• Title: Fire History
• Source: U.S. Geological
Survey
• Note: Fire patterns within
landscape are based on
interactions between
vegetation dynamics, fire
spread, fire effects, and
spatial context.
• 30m resolution
Data Sources
Colorado Fire History
Albers_Conic_Equal_Area
Confidential and Proprietary, Dewberry & Myriad Development, Inc.
7. • Precipitation
• Title: United States
Average Annual
Precipitation
• Source: National
Atlas of the United
States
• 30m resolution
Data Sources
Confidential and Proprietary, Dewberry & Myriad Development, Inc.
Colorado Precipitation
Albers_Conic_Equal_Area
8. • Fuel
• Title: 13 Anderson
Fire Behavior Fuel
Models
• Source: U.S.
Geological Survey
• 30m resolution
Data Sources
Confidential and Proprietary, Dewberry & Myriad Development, Inc.
Colorado Fuel
Albers_Conic_Equal_Area
9. • Slope (Elevation)
• Title: National Elevation
Dataset
• Source: USGS NED
Data Sources
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Colorado Slope
Albers_Conic_Equal_Area
10. • Wind
• Title: National Wind
Resource Assessment
• Source: US Department
of Energy
• Note: Ratings are taken
by wind power density at
10m and 50m
Data Sources
Confidential and Proprietary, Dewberry & Myriad Development, Inc.
Colorado Wind
Albers_Conic_Equal_Area
11. • For every U.S. state*
• Tools Used:
• Define Projection
• Project
• Dissolve
• Clip
• Polygon to Raster
Data Prep
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13. Wind
Fire History
Precipitation
Methodology
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LOW RISK HIGH RISK
SHORT FIRE RETURN INTERVALLONG FIRE RETURN INTERVAL
LOW RISK HIGH RISK
LOW PRECIPITATIONHIGH PRECIPITATION
LOW RISK HIGH RISK
HIGH WIND SPEEDSLOW WIND SPEEDS
14. Factor Influence (%)*
Fuel X
Fire History X
Precipitation X
Wind X
Slope X
Reclassification and Weighted Overlay
* These rankings may be adjusted based on user input
Confidential and Proprietary, Dewberry & Myriad Development, Inc.
Precipitation Range
(average annual in/yr)
Low (1) Medium (2) High (3) Very High (4)
35 to 240 √
20 to 35 √
10 to 20 √
0 to 10 √
3 pillars of wildfire probability
Fuel
Wildfires spread based on the type and quantity of fuel that surrounds it. Fuel can include everything from trees, underbrush and dry grassy fields to homes. The amount of flammable material that surrounds a fire is referred to as the fuel load. Fuel load is measured by the amount of available fuel per unit area, usually tons per acre.
Terrain
The third big influence on wildfire behavior is the lay of the land, or topography. Although it remains virtually unchanged, unlike fuel and weather, topography can either aid or hinder wildfire progression.
Weather
Weather plays a major role in the birth, growth and death of a wildfire. Drought leads to extremely favorable conditions for wildfires, and winds aid a wildfire's progress -- weather can spur the fire to move faster and engulf more land.
From Landfire Government Program through USGS
Frequency
Return interval – time between successive fires
Rotation
Time required to burn an area equal to the area of interest
Spatial Extent
How large and complex are typical fires
Magnitude
Intensity = energy released
Severity = ecological effects
Seasonality
From National Climatic Data Center
Moisture content of fuel is a key indicator of fire
Dryness and drought are huge red flags
From Landfire Government program through USGS
Fuel Type
Vegetation - grass, brush, timber litter or slash
Surface Area-to-Volume ratio by size class and component
Fuel bed depth and moisture of extinction
Live or dead
Landsat/Multi-Resolution Land Characteristics and National Cover Database, USDA forest service inventory and analysis, and National Agricultural Statistics Service
From USGS Data Elevation Model
Key component of the spread of wildfire, rise over run determines how fast a wildfire may grow
From US Department of Energy
Another key component of the spread of wildfire, wind can carry embers over long distances
The environmental factors and their weights can be altered to adapt to changing climate conditions and unforeseen events.
There is plenty of science backing to the model, but it can simply be used as a determination as to whether the home should be inspected or not.
The end result is a model that can eliminate field inspections and empower risk decision making.
This model is 100% driven by GIS protocols, information, and best practices.
It is a dynamic model that can be changed as seen fit.
The weighted fire risk model output is a 30 meter resolution grid.
According to the census bureau, the average size of a zip code is 90 square miles. That means that the granular level of the fire risk model is 250,000 times smaller than average zip code level data.
This is test dataset we used.
Show fire history layer with the inspection data
Going forward, we will develop data triggers that would determine if an inspection is needed. For instance, if vegetation shows a “very high” risk, then we could immediately indicate the home as needing a field inspection. This can be done a number of ways through coding the resulting values.
Quick look at Risk Report
These reports would be created for each structure with an aerial image and a descriptive risk rating for each fire variable as well as an overall risk value
